{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:HDSQLAL3IZNFQ7N5JPJABQESII","short_pith_number":"pith:HDSQLAL3","canonical_record":{"source":{"id":"2207.01723","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-04T21:07:20Z","cross_cats_sorted":[],"title_canon_sha256":"669eb3895de7e3a09f0fbb1ff385bcbb9070c22bdcee1127498aadea83d1c778","abstract_canon_sha256":"c51eb6cc94b13daa56d2921bd3b807c66f103a3a8a70c4b72d8554a1e4daf172"},"schema_version":"1.0"},"canonical_sha256":"38e505817b465a587dbd4bd200c092423c2ab4bd43a82dadb1b6cef568754c6e","source":{"kind":"arxiv","id":"2207.01723","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.01723","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"arxiv_version","alias_value":"2207.01723v3","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.01723","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"pith_short_12","alias_value":"HDSQLAL3IZNF","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"pith_short_16","alias_value":"HDSQLAL3IZNFQ7N5","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"pith_short_8","alias_value":"HDSQLAL3","created_at":"2026-07-05T04:49:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:HDSQLAL3IZNFQ7N5JPJABQESII","target":"record","payload":{"canonical_record":{"source":{"id":"2207.01723","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-04T21:07:20Z","cross_cats_sorted":[],"title_canon_sha256":"669eb3895de7e3a09f0fbb1ff385bcbb9070c22bdcee1127498aadea83d1c778","abstract_canon_sha256":"c51eb6cc94b13daa56d2921bd3b807c66f103a3a8a70c4b72d8554a1e4daf172"},"schema_version":"1.0"},"canonical_sha256":"38e505817b465a587dbd4bd200c092423c2ab4bd43a82dadb1b6cef568754c6e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:49:53.951121Z","signature_b64":"zV8zvznH9JSv+vriKbWnJI9XKOYjQdVhVGd5adEG7iafZLOh/tjsGF3OIcyR8VnCT9XeYRA3QReezPl8vrBVAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"38e505817b465a587dbd4bd200c092423c2ab4bd43a82dadb1b6cef568754c6e","last_reissued_at":"2026-07-05T04:49:53.950767Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:49:53.950767Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.01723","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:49:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CrTQzW5+9oSIoM+b6LnAlVWoVP5fGs04hW+C7IZPJ3w2u33Gk1urZspah6HAait5D/x/5OlRmN9znnoQdRIXCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T07:57:53.183200Z"},"content_sha256":"af586f22c7a208c6de2914c06b7641e18830bc856793d793090efed549a5d1ea","schema_version":"1.0","event_id":"sha256:af586f22c7a208c6de2914c06b7641e18830bc856793d793090efed549a5d1ea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:HDSQLAL3IZNFQ7N5JPJABQESII","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptive Fine-Grained Sketch-Based Image Retrieval","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aneeshan Sain, Animesh Gupta, Ayan Kumar Bhunia, Parth Shah, Pinaki Nath Chowdhury, Tao Xiang, Yi-Zhe Song","submitted_at":"2022-07-04T21:07:20Z","abstract_excerpt":"The recent focus on Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) has shifted towards generalising a model to new categories without any training data from them. In real-world applications, however, a trained FG-SBIR model is often applied to both new categories and different human sketchers, i.e., different drawing styles. Although this complicates the generalisation problem, fortunately, a handful of examples are typically available, enabling the model to adapt to the new category/style. In this paper, we offer a novel perspective -- instead of asking for a model that generalises, we a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.01723","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2207.01723/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:49:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wc4+CeY9FbxJeRL5LHMGje2WnWjAxF3GFbwkhm8SKEMpmFr5txwNWzhsrabaJgP8G3GypG2YnTL6UiFlrMdlDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T07:57:53.183695Z"},"content_sha256":"2ac20ffb7d8edc23e6d116c70b93e0b345bedcafdfbb3d58d8ca97e9d4c30ad7","schema_version":"1.0","event_id":"sha256:2ac20ffb7d8edc23e6d116c70b93e0b345bedcafdfbb3d58d8ca97e9d4c30ad7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HDSQLAL3IZNFQ7N5JPJABQESII/bundle.json","state_url":"https://pith.science/pith/HDSQLAL3IZNFQ7N5JPJABQESII/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HDSQLAL3IZNFQ7N5JPJABQESII/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-11T07:57:53Z","links":{"resolver":"https://pith.science/pith/HDSQLAL3IZNFQ7N5JPJABQESII","bundle":"https://pith.science/pith/HDSQLAL3IZNFQ7N5JPJABQESII/bundle.json","state":"https://pith.science/pith/HDSQLAL3IZNFQ7N5JPJABQESII/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HDSQLAL3IZNFQ7N5JPJABQESII/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:HDSQLAL3IZNFQ7N5JPJABQESII","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"c51eb6cc94b13daa56d2921bd3b807c66f103a3a8a70c4b72d8554a1e4daf172","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-04T21:07:20Z","title_canon_sha256":"669eb3895de7e3a09f0fbb1ff385bcbb9070c22bdcee1127498aadea83d1c778"},"schema_version":"1.0","source":{"id":"2207.01723","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.01723","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"arxiv_version","alias_value":"2207.01723v3","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.01723","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"pith_short_12","alias_value":"HDSQLAL3IZNF","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"pith_short_16","alias_value":"HDSQLAL3IZNFQ7N5","created_at":"2026-07-05T04:49:53Z"},{"alias_kind":"pith_short_8","alias_value":"HDSQLAL3","created_at":"2026-07-05T04:49:53Z"}],"graph_snapshots":[{"event_id":"sha256:2ac20ffb7d8edc23e6d116c70b93e0b345bedcafdfbb3d58d8ca97e9d4c30ad7","target":"graph","created_at":"2026-07-05T04:49:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2207.01723/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The recent focus on Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) has shifted towards generalising a model to new categories without any training data from them. In real-world applications, however, a trained FG-SBIR model is often applied to both new categories and different human sketchers, i.e., different drawing styles. Although this complicates the generalisation problem, fortunately, a handful of examples are typically available, enabling the model to adapt to the new category/style. In this paper, we offer a novel perspective -- instead of asking for a model that generalises, we a","authors_text":"Aneeshan Sain, Animesh Gupta, Ayan Kumar Bhunia, Parth Shah, Pinaki Nath Chowdhury, Tao Xiang, Yi-Zhe Song","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-04T21:07:20Z","title":"Adaptive Fine-Grained Sketch-Based Image Retrieval"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.01723","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:af586f22c7a208c6de2914c06b7641e18830bc856793d793090efed549a5d1ea","target":"record","created_at":"2026-07-05T04:49:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"c51eb6cc94b13daa56d2921bd3b807c66f103a3a8a70c4b72d8554a1e4daf172","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-04T21:07:20Z","title_canon_sha256":"669eb3895de7e3a09f0fbb1ff385bcbb9070c22bdcee1127498aadea83d1c778"},"schema_version":"1.0","source":{"id":"2207.01723","kind":"arxiv","version":3}},"canonical_sha256":"38e505817b465a587dbd4bd200c092423c2ab4bd43a82dadb1b6cef568754c6e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"38e505817b465a587dbd4bd200c092423c2ab4bd43a82dadb1b6cef568754c6e","first_computed_at":"2026-07-05T04:49:53.950767Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:49:53.950767Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zV8zvznH9JSv+vriKbWnJI9XKOYjQdVhVGd5adEG7iafZLOh/tjsGF3OIcyR8VnCT9XeYRA3QReezPl8vrBVAg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:49:53.951121Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.01723","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:af586f22c7a208c6de2914c06b7641e18830bc856793d793090efed549a5d1ea","sha256:2ac20ffb7d8edc23e6d116c70b93e0b345bedcafdfbb3d58d8ca97e9d4c30ad7"],"state_sha256":"705500586d03e53d0561fea83e7e27628920148c9582958e2a871dd39c703d02"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9zgmqOWcgwnvO6vOskLcMUA3B3jJdNb+wUIyJbztT5ZfHJDsVAYlXBKuPgajiRndlH5kGYLXC8hB9N2KCL0EBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T07:57:53.188040Z","bundle_sha256":"12751e6f91ccbec1483237fc42ad31c920c534faaaf5d9c8fb3b7b874480a7a5"}}